Effects of Production Conditions on Yield and Physicochemical Properties of Biochars Produced from Rice Husk and Oil Palm Empty Fruit Bunches

Overview

Journal Environ Sci Pollut Res Int

Publisher Springer

Specialties Environmental Health
Toxicology

Date 2016 Jun 4

PMID 27255313

Citations 1

Authors

Saba Yavari

Amirhossein Malakahmad

Nasiman B Sapari

Affiliations

Soon will be listed here.

Abstract

Biochar is the bio-solid material produced by pyrolysis. The biochar properties are controlled by feedstock and pyrolysis variables. In this study, the impacts of these production variables on biochar yield and physicochemical properties including pH, cation exchange capacity (CEC), total organic carbon (TOC) content, surface area, and pore volume and size were investigated. Rice husk (RH) and oil palm empty fruit bunches (EFB) were used as biomass. The biochars were produced at temperature range of 300 to 700 °C, heating rate of 3 to 10 °C/min and retention time of 1 to 3 h. The pyrolysis conditions were optimized using response surface methodology (RSM) technique to maximize the values of the responses. Analysis of variance (ANOVA) of the results demonstrated that the data fitted well to the linear and quadratic equations. Temperature was found to be the most effective parameter on the responses followed by retention time and heating rate, sequentially. CEC, TOC, surface area, and pore characteristics were evaluated as biochar properties determining their sorption potential. The optimum conditions for the maximum values of the properties were temperatures of 700 and 493.44 °C and time of 3 and 1 h for RH and EFB biochars, respectively. Heating rate at 3 °C/min was found to be the best rate for both biochars. The structure of EFB biomass was more sensitive to heating than rice husk. The biomass type and the production variables were demonstrated as the direct effective factors on biochar yield and physicochemical properties.

Citing Articles

Kinetic, Isotherm and Thermodynamic Aspects of Zn Biosorption by : Optimization of Process Variables by Response Surface Methodology.

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